Soon-Young Jung

Soon-Young Jung


Research Focus & Metrics

Academic Career Length

26Years (2001-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 August 2022 in Molecules and Cells
Verified
Journal Article
Open access
PDF file
HKHyungmin Kim
Hyungmin Kim
JLJeong-Hwa Lee
Jeong-Hwa Lee
SJSoon-Young Jung
Soon-Young Jung
HYHye Hyeon Yun
Hye Hyeon Yun
JKJeong-Heon Ko
Jeong-Heon Ko
JLJeong-Hwa Lee
Jeong-Hwa Lee
Hyungmin Kim, Jeehan Lee, Soon-Young Jung, Hye Hyeon Yun, Jeong-Heon Ko, and Jeong-Hwa Lee. Mol. Cells 2022;45:718-28. https://doi.org/10.14348/molcells.2022.0037

25 July 2018 in Sustainability
Verified
Journal Article
Open access
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HJHong-Jun Jang
Hong-Jun Jang
BKByoungwook Kim
Byoungwook Kim
JKJongwan Kim
Jongwan Kim
SJSoon-Young Jung
Soon-Young Jung
Data mining plays a critical role in sustainable decision-making. Although the k-prototypes algorithm is one of the best-known algorithms for clustering both numeric and categorical data, clustering a large number of spatial objects with mixed numeric and categorical attributes is still inefficient due to complexity. In this paper, we propose an efficient grid-based k-prototypes algorithm, GK-prototypes, which achieves high performance for clustering spatial objects. The first proposed algorithm utilizes both maximum and minimum distance between cluster centers and a cell, which can reduce unnecessary distance calculation. The second proposed algorithm as an extension of the first proposed algorithm, utilizes spatial dependence; spatial data tends to be similar to objects that are close. Each cell has a bitmap index which stores the categorical values of all objects within the same cell for each attribute. This bitmap index can improve performance if the categorical data is skewed. Experimental results show that the proposed algorithms can achieve better performance than the existing pruning techniques of the k-prototypes algorithm.

1 January 2001 in Biological and Pharmaceutical Bulletin
Verified
Journal Article
Open access
KSKyungwon Seo
Kyungwon Seo
SJSoon-Young Jung
Soon-Young Jung
MPMijung Park
Mijung Park
YSYeonjung Song
Yeonjung Song
CSChoung Se-Young
Choung Se-Young
Procyanidolic oligomers (leucocyanidines, LCs) extracted from grape seeds (Vitis vinifera) are known to have antioxidant and antimutagenic activities, and a protective effect against cardiovascular disease. In the present study we examined the influence of LCs on the activities of phase 1 enzymes and conjugation enzymes and on antioxidant enzymes such as superoxide dismutase, catalase, and glutathione peroxidase. Administration of LCs (25, 50, and 100 mg/kg. p.o. for 7 d) markedly decreased the activities of NADPH-cytochrome P450 reductase, P4501A1, P4501A2, and P4503A4, but significantly increased the activities of glutathione S-transferase and phenolsulfotransferase in rat liver. However, the activities of antioxidant enzymes were not affected by LC administration. The inhibition of P450s and increases in phase II enzyme activities indicate a role for LCs as a chemopreventive agent against toxic or carcinogenic metabolites of P450 isozymes.

1 October 2021 in Biochemical and Biophysical Research Communications
Verified
Journal Article
Closed access
SJSoon-Young Jung
Soon-Young Jung
HLHyun Kyoung Lee
Hyun Kyoung Lee
HKHyungmin Kim
Hyungmin Kim
SKSeulki Kim
Seulki Kim
JKJung Soo Kim
Jung Soo Kim
JLJeong-Hwa Lee
Jeong-Hwa Lee

1 February 2014 in Journal of Biomedical Informatics
Verified
Journal Article
Closed access
JCJeongmin Chae
Jeongmin Chae
YJYounghee Jung
Younghee Jung
TLTaemin Lee
Taemin Lee
SJSoon-Young Jung
Soon-Young Jung
CHChan Huh
Chan Huh
HOHeungbum Oh
Heungbum Oh

17 August 2017 in Soft Computing
Verified
Journal Article
Closed access
PDF file
JKJeong-Eun Kim
Jeong-Eun Kim
KPKinam Park
Kinam Park
JCJeong-Min Chae
Jeong-Min Chae
HJHong-Jun Jang
Hong-Jun Jang
BKByoungwook Kim
Byoungwook Kim
SJSoon-Young Jung
Soon-Young Jung